Richard Sowers, a professor of mathematics and industrial and enterprise systems engineering, has developed a model for a smart home that would use real-time energy pricing data to determine the best usage for household appliances.
From an article on the College of Liberal Arts & Sciences website:
“Sowers and his colleagues built a system that crunches a combination of hourly market prices, spot prices (updated every five minutes), and day-ahead prices (determined by energy market prices established a day ahead of time to reduce volatility) to predict the cheapest time to schedule residential loads such as dishwashers, washers, dryers, and the charging of electric vehicles.”
This video helps illustrate the study: